Stan Tsing
Impact in
- Pharmacology top 5%
- Inflammatory mediators and NSAID effects
- Pharmacogenetics and Drug Metabolism
- Biochemistry top 10%
- Eicosanoids and Hypertension Pharmacology
Papers in
-
- Viral Infectious Diseases and Gene Expression in Insects 3
- Melanoma and MAPK Pathways 2
- Glycosylation and Glycoproteins Research 2
- Signaling Pathways in Disease 1
- Genetics 2
- Chronic Lymphocytic Leukemia Research 2
- Co-authors
- Jim Barnett (9 shared papers)Hardy Chan (2 shared papers)Chinh Bach (2 shared papers)David E. Shaw (5 shared papers)Rebecca Mackenzie (1 shared paper)D.H. Ives (1 shared paper)Elliott Sigal (1 shared paper)José Ednésio da Cruz Freire (1 shared paper)
- Journals
- Protein Expression and Purification (2 papers)The Journal of Immunology (1 paper)Journal of Biological Chemistry (1 paper)Bioorganic & Medicinal Chemistry Letters (1 paper)Journal of Molecular Biology (1 paper)
- Partner nations
- United StatesPolandSwitzerland
In The Last Decade
Stan Tsing
10 papers receiving 607 citations
Peers
Comparison fields: 5 of 91
- Pharmacology 215
- Biochemistry 73
- Pharmacology 54
- Genetics 53
- Immunology 102
Countries citing papers authored by Stan Tsing
This map shows the geographic impact of Stan Tsing's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stan Tsing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stan Tsing more than expected).
Fields of papers citing papers by Stan Tsing
This network shows the impact of papers produced by Stan Tsing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stan Tsing. The network helps show where Stan Tsing may publish in the future.
Co-authors
The 25 scholars most cited alongside Stan Tsing, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1994 | 299 | |
| 2 | 2007 | 62 | |
| 3 | 2008 | 50 | |
| 4 | 1996 | 49 | |
| 5 | 2010 | 41 | |
| 6 | 2007 | 37 | |
| 7 | 2010 | 31 | |
| 8 | 1986 | 21 | |
| 9 | 1994 | 21 | |
| 10 | 1995 | 16 |
About Stan Tsing
Stan Tsing is a scholar working on Molecular Biology, Genetics, Animal Science and Zoology, Computational Theory and Mathematics and Immunology, having authored 10 papers that have together received 627 indexed citations. Recurring topics across this work include Viral Infectious Diseases and Gene Expression in Insects (3 papers), Computational Drug Discovery Methods (2 papers), Melanoma and MAPK Pathways (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Glycosylation and Glycoproteins Research (2 papers), Neurobiology and Insect Physiology Research (1 paper), Coccidia and coccidiosis research (1 paper) and Signaling Pathways in Disease (1 paper). The work is most often cited by research in Pharmacology (215 citations), Biochemistry (73 citations), Pharmacology (54 citations), Genetics (53 citations) and Immunology (102 citations). Stan Tsing has collaborated with scholars based in United States, Poland and Switzerland. Frequent co-authors include Jim Barnett, Hardy Chan, Chinh Bach, David E. Shaw, Rebecca Mackenzie, D.H. Ives, Elliott Sigal, José Ednésio da Cruz Freire, C S Ramesha and Joan M. Chow. Their work appears in journals such as Protein Expression and Purification, The Journal of Immunology, Journal of Biological Chemistry, Bioorganic & Medicinal Chemistry Letters and Journal of Molecular Biology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.